* Replication Code for                       
* Madzelan et al. (2025) in Neuroethics
* https://doi.org/10.1007/s12152-025-09606-4



//* [I] Original Data File *//

** Use this dataset for all analyses (use command): Final_pMRI Public Survey Data_Clean_July 2025.dta

** Weights must be set before running analyses using the following code: svyset [pw=weight]

** Set a working directory/folder (cd command) that the regression Excel output files (using outreg2) will save to.




/* [II] Key Variables */

* black_bin (binary variable indicating whether respondent is Black [1]  or Not Black[0])

* hispanic_bin (binary variable indicating whether respondent is Hispanic [1]  or Not Hispanic[0])

* rural_bin_num (binary variable indicating whether respondent is Rural [1]  or Not Rural [0])

* age (continuous variable indicating respondent's age, range 18-89)

* age_groups (categorical variable based on age variable; grouped into 4 levels to match how census reports age)

* age_bin_num (binary variable indicating whether respondent is older than 65 [1] or younger than 65 [0])

* income_combine (continuous variable indicating respodnent's income range, range 1-13)

* economically_disadvantaged (binary variable indicating whether respondent is economically disadvantaged [1] or not [0], based on self-reported zip code, income, and household number)

* mri_familiar_personal (binary variable indicating whether respondent was familiar [1]  or not familiar [0] with MRI)

* distrust_composite2 (continuous variable; range 1-5)

* trust_in_research_bias (continuous variable, range 1-5)

* gender_bin2 (binary variable indicating whether respondent is Male [1] or Female [2]; added as needed for exploratory gender analyses)




/* [III] Sample Statistics - Table 3 */

// Code for producing the percentages used in Table 3 for the sample statistics. The table itself was created in Excel using these numbers.

svyset [pw=weight]

svy: tab gender
svy: tab age_groups_num
svy: tab race_total_hispanic_race_num
svy: tab hispanic_ethnicity_num
svy: tab rural_bin_num
svy: tab education
svy: tab income_vs_census_num
svy: tab health_insurance
svy: tab medicare_coverage

*** Note: For "race_total_hispanic_race", Hispanic and Other were combined in Table 3 to match how the Census reports these data.




/* [IV] Results - Willingness to Participate in pMRI Research - Part 1 */

// Code for producing the means and standard deviations used in Table 4 and Figure 1. The table and figure were then created in Excel.

svyset [pw=weight]

svy: mean participate_you
svy: mean participate_you, over(black_bin)
svy: mean participate_you, over(hispanic_bin)
svy: mean participate_you, over(rural_bin_num)
svy: mean participate_you, over(age_bin_num)
svy: mean participate_you, over(economically_disadvantaged)

svy: mean participate_friend
svy: mean participate_friend, over(black_bin)
svy: mean participate_friend, over(hispanic_bin)
svy: mean participate_friend, over(rural_bin_num)
svy: mean participate_friend, over(age_bin_num)
svy: mean participate_friend, over(economically_disadvantaged)

svy: mean participate_vuladult
svy: mean participate_vuladult, over(black_bin)
svy: mean participate_vuladult, over(hispanic_bin)
svy: mean participate_vuladult, over(rural_bin_num)
svy: mean participate_vuladult, over(age_bin_num)
svy: mean participate_vuladult, over(economically_disadvantaged)

svy: mean participate_7yo
svy: mean participate_7yo, over(black_bin)
svy: mean participate_7yo, over(hispanic_bin)
svy: mean participate_7yo, over(rural_bin_num)
svy: mean participate_7yo, over(age_bin_num)
svy: mean participate_7yo, over(economically_disadvantaged)


// Code for producing the means, standard deviations, and response option percentages in Table S1. The table was then created in Excel.

svyset [pw=weight]

svy: mean participate_you
svy: tab participate_you

svy: mean participate_friend
svy: tab participate_friend

svy: mean participate_vuladult
svy: tab participate_vuladult

svy: mean participate_7yo
svy: tab participate_7yo


// Code for producing the regression output reported in Table S2. The "outreg2" command was used to create a table that was then cleaned up in Excel.

svyset [pw=weight]

svy: reg participate_you i.black_bin i.hispanic_bin i.rural_bin_num c.age c.income_combine i.mri_familiar_personal c.distrust_composite2 c.trust_in_research_bias
outreg2 using willingness_ts2, excel dec(3) stats(coef se pval) alpha(0.001, 0.01, 0.05) symbol(***, **, *)

svy: reg participate_friend i.black_bin i.hispanic_bin i.rural_bin_num c.age c.income_combine i.mri_familiar_personal c.distrust_composite2 c.trust_in_research_bias
outreg2 using willingness_ts2, excel dec(3) stats(coef se pval) alpha(0.001, 0.01, 0.05) symbol(***, **, *)

svy: reg participate_vuladult i.black_bin i.hispanic_bin i.rural_bin_num c.age c.income_combine i.mri_familiar_personal c.distrust_composite2 c.trust_in_research_bias
outreg2 using willingness_ts2, excel dec(3) stats(coef se pval) alpha(0.001, 0.01, 0.05) symbol(***, **, *)

svy: reg participate_7yo i.black_bin i.hispanic_bin i.rural_bin_num c.age c.income_combine i.mri_familiar_personal c.distrust_composite2 c.trust_in_research_bias
outreg2 using willingness_ts2, excel dec(3) stats(coef se pval) alpha(0.001, 0.01, 0.05) symbol(***, **, *)


// Code for producing the regression output reported in Table S9. The "outreg2" command was used to create a table that was then cleaned up in Excel.

svyset [pw=weight]

svy: reg participate_you i.black_bin i.hispanic_bin i.rural_bin_num c.age c.income_combine i.mri_familiar_personal c.distrust_composite2 c.trust_in_research_bias i.gender_bin2
outreg2 using willingness_ts9, excel dec(3) stats(coef se pval) alpha(0.001, 0.01, 0.05) symbol(***, **, *)

svy: reg participate_friend i.black_bin i.hispanic_bin i.rural_bin_num c.age c.income_combine i.mri_familiar_personal c.distrust_composite2 c.trust_in_research_bias i.gender_bin2
outreg2 using willingness_ts9, excel dec(3) stats(coef se pval) alpha(0.001, 0.01, 0.05) symbol(***, **, *)

svy: reg participate_vuladult i.black_bin i.hispanic_bin i.rural_bin_num c.age c.income_combine i.mri_familiar_personal c.distrust_composite2 c.trust_in_research_bias i.gender_bin2
outreg2 using willingness_ts9, excel dec(3) stats(coef se pval) alpha(0.001, 0.01, 0.05) symbol(***, **, *)

svy: reg participate_7yo i.black_bin i.hispanic_bin i.rural_bin_num c.age c.income_combine i.mri_familiar_personal c.distrust_composite2 c.trust_in_research_bias i.gender_bin2
outreg2 using willingness_ts9, excel dec(3) stats(coef se pval) alpha(0.001, 0.01, 0.05) symbol(***, **, *)




/* [V] Results - Willingness to Participate in pMRI Research - Part 2/Influential Factors */

// Code for producing the means found in Figure 2. The figure was created in Excel.

svyset [pw=weight]

svy: mean participate_report
svy: mean participate_report, over(black_bin)
svy: mean participate_report, over(hispanic_bin)
svy: mean participate_report, over(rural_bin_num)
svy: mean participate_report, over(age_bin_num)
svy: mean participate_report, over(economically_disadvantaged)

svy: mean participate_scans
svy: mean participate_scans, over(black_bin)
svy: mean participate_scans, over(hispanic_bin)
svy: mean participate_scans, over(rural_bin_num)
svy: mean participate_scans, over(age_bin_num)
svy: mean participate_scans, over(economically_disadvantaged)

svy: mean participate_home
svy: mean participate_home, over(black_bin)
svy: mean participate_home, over(hispanic_bin)
svy: mean participate_home, over(rural_bin_num)
svy: mean participate_home, over(age_bin_num)
svy: mean participate_home, over(economically_disadvantaged)

svy: mean participate_location
svy: mean participate_location, over(black_bin)
svy: mean participate_location, over(hispanic_bin)
svy: mean participate_location, over(rural_bin_num)
svy: mean participate_location, over(age_bin_num)
svy: mean participate_location, over(economically_disadvantaged)

svy: mean participate_community
svy: mean participate_community, over(black_bin)
svy: mean participate_community, over(hispanic_bin)
svy: mean participate_community, over(rural_bin_num)
svy: mean participate_community, over(age_bin_num)
svy: mean participate_community, over(economically_disadvantaged)

svy: mean participate_minority_scientists
svy: mean participate_minority_scientists, over(black_bin)
svy: mean participate_minority_scientists, over(hispanic_bin)
svy: mean participate_minority_scientists, over(rural_bin_num)
svy: mean participate_minority_scientists, over(age_bin_num)
svy: mean participate_minority_scientists, over(economically_disadvantaged)

svy: mean participate_forprofit
svy: mean participate_forprofit, over(black_bin)
svy: mean participate_forprofit, over(hispanic_bin)
svy: mean participate_forprofit, over(rural_bin_num)
svy: mean participate_forprofit, over(age_bin_num)
svy: mean participate_forprofit, over(economically_disadvantaged)

svy: mean participate_injection
svy: mean participate_injection, over(black_bin)
svy: mean participate_injection, over(hispanic_bin)
svy: mean participate_injection, over(rural_bin_num)
svy: mean participate_injection, over(age_bin_num)
svy: mean participate_injection, over(economically_disadvantaged)

svy: mean participate_hospital_travel
svy: mean participate_hospital_travel, over(black_bin)
svy: mean participate_hospital_travel, over(hispanic_bin)
svy: mean participate_hospital_travel, over(rural_bin_num)
svy: mean participate_hospital_travel, over(age_bin_num)
svy: mean participate_hospital_travel, over(economically_disadvantaged)


// Code for producing the means, standard deviations, and response option percentages in Table S3. The table was then created in Excel.

svyset [pw=weight]

svy: mean participate_report
svy: tab participate_report

svy: mean participate_scans
svy: tab participate_scans

svy: mean participate_home
svy: tab participate_home

svy: mean participate_location
svy: tab participate_location

svy: mean participate_community
svy: tab participate_community

svy: mean participate_minority_scientists
svy: tab participate_minority_scientists

svy: mean participate_forprofit
svy: tab participate_forprofit

svy: mean participate_injection
svy: tab participate_injection

svy: mean participate_hospital_travel
svy: tab participate_hospital_travel


// Code for producing the regression output reported in Table S4. The "outreg2" command was used to create a table that was then cleaned up in Excel.

svyset [pw=weight]

svy: reg participate_report i.black_bin i.hispanic_bin i.rural_bin_num c.age c.income_combine i.mri_familiar_personal c.distrust_composite2 c.trust_in_research_bias
outreg2 using willingness_ts4, excel dec(3) stats(coef se pval) alpha(0.001, 0.01, 0.05) symbol(***, **, *)

svy: reg participate_scans i.black_bin i.hispanic_bin i.rural_bin_num c.age c.income_combine i.mri_familiar_personal c.distrust_composite2 c.trust_in_research_bias
outreg2 using willingness_ts4, excel append dec(3) stats(coef se pval) alpha(0.001, 0.01, 0.05) symbol(***, **, *)

svy: reg participate_home i.black_bin i.hispanic_bin i.rural_bin_num c.age c.income_combine i.mri_familiar_personal c.distrust_composite2 c.trust_in_research_bias
outreg2 using willingness_ts4, excel append dec(3) stats(coef se pval) alpha(0.001, 0.01, 0.05) symbol(***, **, *)

svy: reg participate_location i.black_bin i.hispanic_bin i.rural_bin_num c.age c.income_combine i.mri_familiar_personal c.distrust_composite2 c.trust_in_research_bias
outreg2 using willingness_ts4, excel append dec(3) stats(coef se pval) alpha(0.001, 0.01, 0.05) symbol(***, **, *)

svy: reg participate_community i.black_bin i.hispanic_bin i.rural_bin_num c.age c.income_combine i.mri_familiar_personal c.distrust_composite2 c.trust_in_research_bias
outreg2 using willingness_ts4, excel append dec(3) stats(coef se pval) alpha(0.001, 0.01, 0.05) symbol(***, **, *)

svy: reg participate_minority_scientists i.black_bin i.hispanic_bin i.rural_bin_num c.age c.income_combine i.mri_familiar_personal c.distrust_composite2 c.trust_in_research_bias
outreg2 using willingness_ts4, excel append dec(3) stats(coef se pval) alpha(0.001, 0.01, 0.05) symbol(***, **, *)

svy: reg participate_forprofit i.black_bin i.hispanic_bin i.rural_bin_num c.age c.income_combine i.mri_familiar_personal c.distrust_composite2 c.trust_in_research_bias
outreg2 using willingness_ts4, excel append dec(3) stats(coef se pval) alpha(0.001, 0.01, 0.05) symbol(***, **, *)

svy: reg participate_injection i.black_bin i.hispanic_bin i.rural_bin_num c.age c.income_combine i.mri_familiar_personal c.distrust_composite2 c.trust_in_research_bias
outreg2 using willingness_ts4, excel append dec(3) stats(coef se pval) alpha(0.001, 0.01, 0.05) symbol(***, **, *)

svy: reg participate_hospital_travel i.black_bin i.hispanic_bin i.rural_bin_num c.age c.income_combine i.mri_familiar_personal c.distrust_composite2 c.trust_in_research_bias
outreg2 using willingness_ts4, excel append dec(3) stats(coef se pval) alpha(0.001, 0.01, 0.05) symbol(***, **, *)


// Code for producing the regression output reported in Table S10. The "outreg2" command was used to create a table that was then cleaned up in Excel.

svyset [pw=weight]

svy: reg participate_report i.black_bin i.hispanic_bin i.rural_bin_num c.age c.income_combine i.mri_familiar_personal c.distrust_composite2 c.trust_in_research_bias i.gender_bin2
outreg2 using willingness_ts10, excel dec(3) stats(coef se pval) alpha(0.001, 0.01, 0.05) symbol(***, **, *)

svy: reg participate_scans i.black_bin i.hispanic_bin i.rural_bin_num c.age c.income_combine i.mri_familiar_personal c.distrust_composite2 c.trust_in_research_bias i.gender_bin2
outreg2 using willingness_ts10, excel append dec(3) stats(coef se pval) alpha(0.001, 0.01, 0.05) symbol(***, **, *)

svy: reg participate_home i.black_bin i.hispanic_bin i.rural_bin_num c.age c.income_combine i.mri_familiar_personal c.distrust_composite2 c.trust_in_research_bias i.gender_bin2
outreg2 using willingness_ts10, excel append dec(3) stats(coef se pval) alpha(0.001, 0.01, 0.05) symbol(***, **, *)

svy: reg participate_location i.black_bin i.hispanic_bin i.rural_bin_num c.age c.income_combine i.mri_familiar_personal c.distrust_composite2 c.trust_in_research_bias i.gender_bin2
outreg2 using willingness_ts10, excel append dec(3) stats(coef se pval) alpha(0.001, 0.01, 0.05) symbol(***, **, *)

svy: reg participate_community i.black_bin i.hispanic_bin i.rural_bin_num c.age c.income_combine i.mri_familiar_personal c.distrust_composite2 c.trust_in_research_bias i.gender_bin2
outreg2 using willingness_ts10, excel append dec(3) stats(coef se pval) alpha(0.001, 0.01, 0.05) symbol(***, **, *)

svy: reg participate_minority_scientists i.black_bin i.hispanic_bin i.rural_bin_num c.age c.income_combine i.mri_familiar_personal c.distrust_composite2 c.trust_in_research_bias i.gender_bin2
outreg2 using willingness_ts10, excel append dec(3) stats(coef se pval) alpha(0.001, 0.01, 0.05) symbol(***, **, *)

svy: reg participate_forprofit i.black_bin i.hispanic_bin i.rural_bin_num c.age c.income_combine i.mri_familiar_personal c.distrust_composite2 c.trust_in_research_bias i.gender_bin2
outreg2 using willingness_ts10, excel append dec(3) stats(coef se pval) alpha(0.001, 0.01, 0.05) symbol(***, **, *)

svy: reg participate_injection i.black_bin i.hispanic_bin i.rural_bin_num c.age c.income_combine i.mri_familiar_personal c.distrust_composite2 c.trust_in_research_bias i.gender_bin2
outreg2 using willingness_ts10, excel append dec(3) stats(coef se pval) alpha(0.001, 0.01, 0.05) symbol(***, **, *)

svy: reg participate_hospital_travel i.black_bin i.hispanic_bin i.rural_bin_num c.age c.income_combine i.mri_familiar_personal c.distrust_composite2 c.trust_in_research_bias i.gender_bin2
outreg2 using willingness_ts10, excel append dec(3) stats(coef se pval) alpha(0.001, 0.01, 0.05) symbol(***, **, *)




/* [VI] Results - Potential Benefits */

// Code for producing the means found in Figure 3. The figure was created in Excel.

svyset [pw=weight]

svy: mean benefits_followup_info
svy: mean benefits_followup_info, over(black_bin)
svy: mean benefits_followup_info, over(hispanic_bin)
svy: mean benefits_followup_info, over(rural_bin_num)
svy: mean benefits_followup_info, over(age_bin_num)
svy: mean benefits_followup_info, over(economically_disadvantaged)

svy: mean benefits_learn_condition
svy: mean benefits_learn_condition, over(black_bin)
svy: mean benefits_learn_condition, over(hispanic_bin)
svy: mean benefits_learn_condition, over(rural_bin_num)
svy: mean benefits_learn_condition, over(age_bin_num)
svy: mean benefits_learn_condition, over(economically_disadvantaged)

svy: mean benefits_learn_brain
svy: mean benefits_learn_brain, over(black_bin)
svy: mean benefits_learn_brain, over(hispanic_bin)
svy: mean benefits_learn_brain, over(rural_bin_num)
svy: mean benefits_learn_brain, over(age_bin_num)
svy: mean benefits_learn_brain, over(economically_disadvantaged)

svy: mean benefits_payment
svy: mean benefits_payment, over(black_bin)
svy: mean benefits_payment, over(hispanic_bin)
svy: mean benefits_payment, over(rural_bin_num)
svy: mean benefits_payment, over(age_bin_num)
svy: mean benefits_payment, over(economically_disadvantaged)

svy: mean benefits_help_others
svy: mean benefits_help_others, over(black_bin)
svy: mean benefits_help_others, over(hispanic_bin)
svy: mean benefits_help_others, over(rural_bin_num)
svy: mean benefits_help_others, over(age_bin_num)
svy: mean benefits_help_others, over(economically_disadvantaged)

svy: mean benefits_science
svy: mean benefits_science, over(black_bin)
svy: mean benefits_science, over(hispanic_bin)
svy: mean benefits_science, over(rural_bin_num)
svy: mean benefits_science, over(age_bin_num)
svy: mean benefits_science, over(economically_disadvantaged)

svy: mean benefits_treatment
svy: mean benefits_treatment, over(black_bin)
svy: mean benefits_treatment, over(hispanic_bin)
svy: mean benefits_treatment, over(rural_bin_num)
svy: mean benefits_treatment, over(age_bin_num)
svy: mean benefits_treatment, over(economically_disadvantaged)

svy: mean benefits_coolpic
svy: mean benefits_coolpic, over(black_bin)
svy: mean benefits_coolpic, over(hispanic_bin)
svy: mean benefits_coolpic, over(rural_bin_num)
svy: mean benefits_coolpic, over(age_bin_num)
svy: mean benefits_coolpic, over(economically_disadvantaged)

svy: mean benefits_interesting
svy: mean benefits_interesting, over(black_bin)
svy: mean benefits_interesting, over(hispanic_bin)
svy: mean benefits_interesting, over(rural_bin_num)
svy: mean benefits_interesting, over(age_bin_num)
svy: mean benefits_interesting, over(economically_disadvantaged)


// Code for producing the means, standard deviations, and response option percentages in Table S5. The table was then created in Excel.

svyset [pw=weight]

svy: mean benefits_followup_info
svy: tab benefits_followup_info

svy: mean benefits_learn_condition
svy: tab benefits_learn_condition

svy: mean benefits_learn_brain
svy: tab benefits_learn_brain

svy: mean benefits_payment
svy: tab benefits_payment

svy: mean benefits_help_others
svy: tab benefits_help_others

svy: mean benefits_science
svy: tab benefits_science

svy: mean benefits_treatment
svy: tab benefits_treatment

svy: mean benefits_coolpic
svy: tab benefits_coolpic

svy: mean benefits_interesting
svy: tab benefits_interesting


// Code for producing the regression output reported in Table S6. The "outreg2" command was used to create a table that was then cleaned up in Excel.

svyset [pw=weight]

svy: reg benefits_followup_info i.black_bin i.hispanic_bin i.rural_bin_num c.age c.income_combine i.mri_familiar_personal c.distrust_composite2 c.trust_in_research_bias
outreg2 using benefits_ts6, excel dec(3) stats(coef se pval) alpha(0.001, 0.01, 0.05) symbol(***, **, *)

svy: reg benefits_learn_condition i.black_bin i.hispanic_bin i.rural_bin_num c.age c.income_combine i.mri_familiar_personal c.distrust_composite2 c.trust_in_research_bias
outreg2 using benefits_ts6, excel append dec(3) stats(coef se pval) alpha(0.001, 0.01, 0.05) symbol(***, **, *)

svy: reg benefits_learn_brain i.black_bin i.hispanic_bin i.rural_bin_num c.age c.income_combine i.mri_familiar_personal c.distrust_composite2 c.trust_in_research_bias
outreg2 using benefits_ts6, excel append dec(3) stats(coef se pval) alpha(0.001, 0.01, 0.05) symbol(***, **, *)

svy: reg benefits_payment i.black_bin i.hispanic_bin i.rural_bin_num c.age c.income_combine i.mri_familiar_personal c.distrust_composite2 c.trust_in_research_bias
outreg2 using benefits_ts6, excel append dec(3) stats(coef se pval) alpha(0.001, 0.01, 0.05) symbol(***, **, *)

svy: reg benefits_help_others i.black_bin i.hispanic_bin i.rural_bin_num c.age c.income_combine i.mri_familiar_personal c.distrust_composite2 c.trust_in_research_bias
outreg2 using benefits_ts6, excel append dec(3) stats(coef se pval) alpha(0.001, 0.01, 0.05) symbol(***, **, *)

svy: reg benefits_science i.black_bin i.hispanic_bin i.rural_bin_num c.age c.income_combine i.mri_familiar_personal c.distrust_composite2 c.trust_in_research_bias
outreg2 using benefits_ts6, excel append dec(3) stats(coef se pval) alpha(0.001, 0.01, 0.05) symbol(***, **, *)

svy: reg benefits_treatment i.black_bin i.hispanic_bin i.rural_bin_num c.age c.income_combine i.mri_familiar_personal c.distrust_composite2 c.trust_in_research_bias
outreg2 using benefits_ts6, excel append dec(3) stats(coef se pval) alpha(0.001, 0.01, 0.05) symbol(***, **, *)

svy: reg benefits_coolpic i.black_bin i.hispanic_bin i.rural_bin_num c.age c.income_combine i.mri_familiar_personal c.distrust_composite2 c.trust_in_research_bias
outreg2 using benefits_ts6, excel append dec(3) stats(coef se pval) alpha(0.001, 0.01, 0.05) symbol(***, **, *)

svy: reg benefits_interesting i.black_bin i.hispanic_bin i.rural_bin_num c.age c.income_combine i.mri_familiar_personal c.distrust_composite2 c.trust_in_research_bias
outreg2 using benefits_ts6, excel append dec(3) stats(coef se pval) alpha(0.001, 0.01, 0.05) symbol(***, **, *)


// Code for producing the regression output reported in Table S11. The "outreg2" command was used to create a table that was then cleaned up in Excel.

svyset [pw=weight]

svy: reg benefits_followup_info i.black_bin i.hispanic_bin i.rural_bin_num c.age c.income_combine i.mri_familiar_personal c.distrust_composite2 c.trust_in_research_bias i.gender_bin2
outreg2 using benefits_ts11, excel dec(3) stats(coef se pval) alpha(0.001, 0.01, 0.05) symbol(***, **, *)

svy: reg benefits_learn_condition i.black_bin i.hispanic_bin i.rural_bin_num c.age c.income_combine i.mri_familiar_personal c.distrust_composite2 c.trust_in_research_bias i.gender_bin2
outreg2 using benefits_ts11, excel append dec(3) stats(coef se pval) alpha(0.001, 0.01, 0.05) symbol(***, **, *)

svy: reg benefits_learn_brain i.black_bin i.hispanic_bin i.rural_bin_num c.age c.income_combine i.mri_familiar_personal c.distrust_composite2 c.trust_in_research_bias i.gender_bin2
outreg2 using benefits_ts11, excel append dec(3) stats(coef se pval) alpha(0.001, 0.01, 0.05) symbol(***, **, *)

svy: reg benefits_payment i.black_bin i.hispanic_bin i.rural_bin_num c.age c.income_combine i.mri_familiar_personal c.distrust_composite2 c.trust_in_research_bias i.gender_bin2
outreg2 using benefits_ts11, excel append dec(3) stats(coef se pval) alpha(0.001, 0.01, 0.05) symbol(***, **, *)

svy: reg benefits_help_others i.black_bin i.hispanic_bin i.rural_bin_num c.age c.income_combine i.mri_familiar_personal c.distrust_composite2 c.trust_in_research_bias i.gender_bin2
outreg2 using benefits_ts11, excel append dec(3) stats(coef se pval) alpha(0.001, 0.01, 0.05) symbol(***, **, *)

svy: reg benefits_science i.black_bin i.hispanic_bin i.rural_bin_num c.age c.income_combine i.mri_familiar_personal c.distrust_composite2 c.trust_in_research_bias i.gender_bin2
outreg2 using benefits_ts11, excel append dec(3) stats(coef se pval) alpha(0.001, 0.01, 0.05) symbol(***, **, *)

svy: reg benefits_treatment i.black_bin i.hispanic_bin i.rural_bin_num c.age c.income_combine i.mri_familiar_personal c.distrust_composite2 c.trust_in_research_bias i.gender_bin2
outreg2 using benefits_ts11, excel append dec(3) stats(coef se pval) alpha(0.001, 0.01, 0.05) symbol(***, **, *)

svy: reg benefits_coolpic i.black_bin i.hispanic_bin i.rural_bin_num c.age c.income_combine i.mri_familiar_personal c.distrust_composite2 c.trust_in_research_bias i.gender_bin2
outreg2 using benefits_ts11, excel append dec(3) stats(coef se pval) alpha(0.001, 0.01, 0.05) symbol(***, **, *)

svy: reg benefits_interesting i.black_bin i.hispanic_bin i.rural_bin_num c.age c.income_combine i.mri_familiar_personal c.distrust_composite2 c.trust_in_research_bias i.gender_bin2
outreg2 using benefits_ts11, excel append dec(3) stats(coef se pval) alpha(0.001, 0.01, 0.05) symbol(***, **, *)





/* [VI] Results - Potential Concerns */

// Code for producing the means found in Figure 4. The figure was created in Excel.

svyset [pw=weight]

svy: mean concern_payment
svy: mean concern_payment, over(black_bin)
svy: mean concern_payment, over(hispanic_bin)
svy: mean concern_payment, over(rural_bin_num)
svy: mean concern_payment, over(age_bin_num)
svy: mean concern_payment, over(economically_disadvantaged)

svy: mean concern_insurance
svy: mean concern_insurance, over(black_bin)
svy: mean concern_insurance, over(hispanic_bin)
svy: mean concern_insurance, over(rural_bin_num)
svy: mean concern_insurance, over(age_bin_num)
svy: mean concern_insurance, over(economically_disadvantaged)

svy: mean concern_privacy
svy: mean concern_privacy, over(black_bin)
svy: mean concern_privacy, over(hispanic_bin)
svy: mean concern_privacy, over(rural_bin_num)
svy: mean concern_privacy, over(age_bin_num)
svy: mean concern_privacy, over(economically_disadvantaged)

svy: mean concern_safety
svy: mean concern_safety, over(black_bin)
svy: mean concern_safety, over(hispanic_bin)
svy: mean concern_safety, over(rural_bin_num)
svy: mean concern_safety, over(age_bin_num)
svy: mean concern_safety, over(economically_disadvantaged)

svy: mean concern_metal_body
svy: mean concern_metal_body, over(black_bin)
svy: mean concern_metal_body, over(hispanic_bin)
svy: mean concern_metal_body, over(rural_bin_num)
svy: mean concern_metal_body, over(age_bin_num)
svy: mean concern_metal_body, over(economically_disadvantaged)

svy: mean concern_something_wrong
svy: mean concern_something_wrong, over(black_bin)
svy: mean concern_something_wrong, over(hispanic_bin)
svy: mean concern_something_wrong, over(rural_bin_num)
svy: mean concern_something_wrong, over(age_bin_num)
svy: mean concern_something_wrong, over(economically_disadvantaged)

svy: mean concern_trust
svy: mean concern_trust, over(black_bin)
svy: mean concern_trust, over(hispanic_bin)
svy: mean concern_trust, over(rural_bin_num)
svy: mean concern_trust, over(age_bin_num)
svy: mean concern_trust, over(economically_disadvantaged)

svy: mean concern_time
svy: mean concern_time, over(black_bin)
svy: mean concern_time, over(hispanic_bin)
svy: mean concern_time, over(rural_bin_num)
svy: mean concern_time, over(age_bin_num)
svy: mean concern_time, over(economically_disadvantaged)

svy: mean concern_discomfort
svy: mean concern_discomfort, over(black_bin)
svy: mean concern_discomfort, over(hispanic_bin)
svy: mean concern_discomfort, over(rural_bin_num)
svy: mean concern_discomfort, over(age_bin_num)
svy: mean concern_discomfort, over(economically_disadvantaged)

svy: mean concern_values
svy: mean concern_values, over(black_bin)
svy: mean concern_values, over(hispanic_bin)
svy: mean concern_values, over(rural_bin_num)
svy: mean concern_values, over(age_bin_num)
svy: mean concern_values, over(economically_disadvantaged)

svy: mean concern_mindcontrol
svy: mean concern_mindcontrol, over(black_bin)
svy: mean concern_mindcontrol, over(hispanic_bin)
svy: mean concern_mindcontrol, over(rural_bin_num)
svy: mean concern_mindcontrol, over(age_bin_num)
svy: mean concern_mindcontrol, over(economically_disadvantaged)


// Code for producing the means, standard deviations, and response option percentages in Table S7. The table was then created in Excel.

svyset [pw=weight]

svy: mean concern_payment
svy: tab concern_payment

svy: mean concern_insurance
svy: tab concern_insurance

svy: mean concern_privacy
svy: tab concern_privacy

svy: mean concern_safety
svy: tab concern_safety

svy: mean concern_metal_body
svy: tab concern_metal_body

svy: mean concern_something_wrong
svy: tab concern_something_wrong

svy: mean concern_trust
svy: tab concern_trust

svy: mean concern_time
svy: tab concern_time

svy: mean concern_discomfort
svy: tab concern_discomfort

svy: mean concern_values
svy: tab concern_values

svy: mean concern_mindcontrol
svy: tab concern_mindcontrol


// Code for producing the regression output reported in Table S8. The "outreg2" command was used to create a table that was then cleaned up in Excel.

svyset [pw=weight]

svy: reg concern_payment i.black_bin i.hispanic_bin i.rural_bin_num c.age c.income_combine i.mri_familiar_personal c.distrust_composite2 c.trust_in_research_bias
outreg2 using concerns_ts8, excel dec(3) stats(coef se pval) alpha(0.001, 0.01, 0.05) symbol(***, **, *)

svy: reg concern_insurance i.black_bin i.hispanic_bin i.rural_bin_num c.age c.income_combine i.mri_familiar_personal c.distrust_composite2 c.trust_in_research_bias
outreg2 using concerns_ts8, excel append dec(3) stats(coef se pval) alpha(0.001, 0.01, 0.05) symbol(***, **, *)

svy: reg concern_privacy i.black_bin i.hispanic_bin i.rural_bin_num c.age c.income_combine i.mri_familiar_personal c.distrust_composite2 c.trust_in_research_bias
outreg2 using concerns_ts8, excel append dec(3) stats(coef se pval) alpha(0.001, 0.01, 0.05) symbol(***, **, *)

svy: reg concern_safety i.black_bin i.hispanic_bin i.rural_bin_num c.age c.income_combine i.mri_familiar_personal c.distrust_composite2 c.trust_in_research_bias
outreg2 using concerns_ts8, excel append dec(3) stats(coef se pval) alpha(0.001, 0.01, 0.05) symbol(***, **, *)

svy: reg concern_metal_body i.black_bin i.hispanic_bin i.rural_bin_num c.age c.income_combine i.mri_familiar_personal c.distrust_composite2 c.trust_in_research_bias
outreg2 using concerns_ts8, excel append dec(3) stats(coef se pval) alpha(0.001, 0.01, 0.05) symbol(***, **, *)

svy: reg concern_something_wrong i.black_bin i.hispanic_bin i.rural_bin_num c.age c.income_combine i.mri_familiar_personal c.distrust_composite2 c.trust_in_research_bias
outreg2 using concerns_ts8, excel append dec(3) stats(coef se pval) alpha(0.001, 0.01, 0.05) symbol(***, **, *)

svy: reg concern_trust i.black_bin i.hispanic_bin i.rural_bin_num c.age c.income_combine i.mri_familiar_personal c.distrust_composite2 c.trust_in_research_bias
outreg2 using concerns_ts8, excel append dec(3) stats(coef se pval) alpha(0.001, 0.01, 0.05) symbol(***, **, *)

svy: reg concern_time i.black_bin i.hispanic_bin i.rural_bin_num c.age c.income_combine i.mri_familiar_personal c.distrust_composite2 c.trust_in_research_bias
outreg2 using concerns_ts8, excel append dec(3) stats(coef se pval) alpha(0.001, 0.01, 0.05) symbol(***, **, *)

svy: reg concern_discomfort i.black_bin i.hispanic_bin i.rural_bin_num c.age c.income_combine i.mri_familiar_personal c.distrust_composite2 c.trust_in_research_bias
outreg2 using concerns_ts8, excel append dec(3) stats(coef se pval) alpha(0.001, 0.01, 0.05) symbol(***, **, *)

svy: reg concern_values i.black_bin i.hispanic_bin i.rural_bin_num c.age c.income_combine i.mri_familiar_personal c.distrust_composite2 c.trust_in_research_bias
outreg2 using concerns_ts8, excel append dec(3) stats(coef se pval) alpha(0.001, 0.01, 0.05) symbol(***, **, *)

svy: reg concern_mindcontrol i.black_bin i.hispanic_bin i.rural_bin_num c.age c.income_combine i.mri_familiar_personal c.distrust_composite2 c.trust_in_research_bias
outreg2 using concerns_ts8, excel append dec(3) stats(coef se pval) alpha(0.001, 0.01, 0.05) symbol(***, **, *)


// Code for producing the regression output reported in Table S12. The "outreg2" command was used to create a table that was then cleaned up in Excel.

svyset [pw=weight]

svy: reg concern_payment i.black_bin i.hispanic_bin i.rural_bin_num c.age c.income_combine i.mri_familiar_personal c.distrust_composite2 c.trust_in_research_bias i.gender_bin2
outreg2 using concerns_ts12, excel dec(3) stats(coef se pval) alpha(0.001, 0.01, 0.05) symbol(***, **, *)

svy: reg concern_insurance i.black_bin i.hispanic_bin i.rural_bin_num c.age c.income_combine i.mri_familiar_personal c.distrust_composite2 c.trust_in_research_bias i.gender_bin2
outreg2 using concerns_ts12, excel append dec(3) stats(coef se pval) alpha(0.001, 0.01, 0.05) symbol(***, **, *)

svy: reg concern_privacy i.black_bin i.hispanic_bin i.rural_bin_num c.age c.income_combine i.mri_familiar_personal c.distrust_composite2 c.trust_in_research_bias i.gender_bin2
outreg2 using concerns_ts12, excel append dec(3) stats(coef se pval) alpha(0.001, 0.01, 0.05) symbol(***, **, *)

svy: reg concern_safety i.black_bin i.hispanic_bin i.rural_bin_num c.age c.income_combine i.mri_familiar_personal c.distrust_composite2 c.trust_in_research_bias i.gender_bin2
outreg2 using concerns_ts12, excel append dec(3) stats(coef se pval) alpha(0.001, 0.01, 0.05) symbol(***, **, *)

svy: reg concern_metal_body i.black_bin i.hispanic_bin i.rural_bin_num c.age c.income_combine i.mri_familiar_personal c.distrust_composite2 c.trust_in_research_bias i.gender_bin2
outreg2 using concerns_ts12, excel append dec(3) stats(coef se pval) alpha(0.001, 0.01, 0.05) symbol(***, **, *)

svy: reg concern_something_wrong i.black_bin i.hispanic_bin i.rural_bin_num c.age c.income_combine i.mri_familiar_personal c.distrust_composite2 c.trust_in_research_bias i.gender_bin2
outreg2 using concerns_ts12, excel append dec(3) stats(coef se pval) alpha(0.001, 0.01, 0.05) symbol(***, **, *)

svy: reg concern_trust i.black_bin i.hispanic_bin i.rural_bin_num c.age c.income_combine i.mri_familiar_personal c.distrust_composite2 c.trust_in_research_bias i.gender_bin2
outreg2 using concerns_ts12, excel append dec(3) stats(coef se pval) alpha(0.001, 0.01, 0.05) symbol(***, **, *)

svy: reg concern_time i.black_bin i.hispanic_bin i.rural_bin_num c.age c.income_combine i.mri_familiar_personal c.distrust_composite2 c.trust_in_research_bias i.gender_bin2
outreg2 using concerns_ts12, excel append dec(3) stats(coef se pval) alpha(0.001, 0.01, 0.05) symbol(***, **, *)

svy: reg concern_discomfort i.black_bin i.hispanic_bin i.rural_bin_num c.age c.income_combine i.mri_familiar_personal c.distrust_composite2 c.trust_in_research_bias i.gender_bin2
outreg2 using concerns_ts12, excel append dec(3) stats(coef se pval) alpha(0.001, 0.01, 0.05) symbol(***, **, *)

svy: reg concern_values i.black_bin i.hispanic_bin i.rural_bin_num c.age c.income_combine i.mri_familiar_personal c.distrust_composite2 c.trust_in_research_bias i.gender_bin2
outreg2 using concerns_ts12, excel append dec(3) stats(coef se pval) alpha(0.001, 0.01, 0.05) symbol(***, **, *)

svy: reg concern_mindcontrol i.black_bin i.hispanic_bin i.rural_bin_num c.age c.income_combine i.mri_familiar_personal c.distrust_composite2 c.trust_in_research_bias i.gender_bin2
outreg2 using concerns_ts12, excel append dec(3) stats(coef se pval) alpha(0.001, 0.01, 0.05) symbol(***, **, *)




